Background: In Puerto Rico (PR), cancer is the second leading cause
of death and the disease that causes most premature deaths, representing
about 15% of them. Thus, premature death due to cancer decreases the
productivity capacity in PR.

Objective: This study aimed to estimate the labor-market
productivity loss in PR during 2004 as a result of premature mortality
due to overall cancer and cause-specific cancers.

Methods: A model based in the incidence-based approach and in the
human capital approach was developed to estimate the labor-market
productivity loss. Economic data were obtained from the Public Use
Microdata Sample (PUMS) of the PR Community Survey (PRCS). Mortality
data were obtained from the Vital Statistics of the PR Department of
Health.

Results: The productivity costs of all cancer deaths were estimated
to be approximately $64 million (in constant value). The cancer deaths
that contributed the most to productivity loss were lung and bronchus,
colorectal, breast, and liver and intrahepatic bile duct.

Conclusions: Although these results must be interpreted with
caution, this study contributes to show a broader picture that includes
the economic dimension of cancer in our society. These estimates imply
that productivity cost due to cancer mortality have a great burden in
PR. The leading cancer sites that generate most productivity losses are
highly preventable or can be diagnosed early or are related to tobacco
consumption. This study should be considered within the framework of
future cost analyses for the development of health and cancer control
policies.

Cancer is a leading cause of death worldwide, accounting for 7.4
million deaths (around 13% of all deaths) in 2004 (1). In Puerto Rico
(PR), cancer is the second leading cause of death and the disease that
causes most premature deaths, representing about 15% of them (2).
Besides being a clinical problem, disease and death comprehend other
social issues, including economic aspects that cause a significant
burden to society. Therefore, premature death due to cancer represents
an impairment of labor, a valuable economic resource, that prevents a
person from contributing productively to society in the future,
decreasing its productivity capacity.

Economic theory provides different methods to assess the economic
impact of a health condition, as is cancer. The Cost of Illness (COI),
developed by Rice (3-6), is the most widely accepted conceptual
framework for cost estimates. COI estimates involve three components:
direct costs, morbidity costs and mortality costs. Within this
framework, several studies with different approaches have been conducted
to determine the economic burden of different diseases (7-17). These
studies have concluded that the component with the greatest impact lies
in the productivity cost, even more than the costs for medical treatment
of patients. For example, the National Institutes of Health(18)
estimated the cost of illness for different causes of death in United
States (US) for 2007. This study estimated the overall cost of cancer at
$219.2 billion, of which, $89 billion correspond to direct costs of
health expenditure, $18.2 billion in morbidity costs and $112.0 billion
in mortality costs (representing more than 52% of total costs). Others
studies of the economic burden of cancer in California (14-15) have
concluded that the premature mortality cost of breast cancer is 80% of
the total costs of the disease. Also, mortality costs of gynecological
cancers like ovarian and cervical cancer represent more than 65% of
total cost of these cancers. This pattern has also been observed in the
state of Texas and in Sweden, Canada, and Spain (10-11, 17, 19-20).
Other studies (20-25) have focused on estimating the productivity cost
due to cancer mortality. Although these studies show some discrepancies
in their methodology, data sources, and the inclusion of indirect costs
components, such variations are not necessarily a weakness. Different
arenas of application require different approaches and schemes (e.g.,
economic burden estimates vs. cost-effectiveness analysis) (4-5, 26).

From a societal perspective, estimates of the value of labor
productivity loss due to premature mortality are important in
determining the economic burden of disease. Previous studies in PR have
used the COI approach to estimate the cost of AIDS, schizophrenia and
traffic accidents (7, 27-28). For example, cumulative total cost of AIDS
in PR from period of 19821989 was estimated to be $ 525.2 million (27).
Despite the importance of evaluating the economic impact of cancer in
PR, there are no previous studies that have used the COI approach to
investigate this issue. In fact, this economic component has been
overlooked in cancer investigations in PR. Although the value of a
person's life transcends its economic value as a productive unit,
cost studies present another dimension of a health problem, providing
valuable information for society and for policymakers to decide how to
allocate scarce resources more optimally (27). Consequently, the aim of
this study is to estimate the labor-market productivity loss in PR, as a
result of premature mortality, due to overall cancer and by
cause-specific cancers in 2004.

Methods

Model

COI studies may consider different timeframes for cost estimation.
Two recognized models for establishing a time frame have been used in
COI studies: the prevalence-based model and the incidence-based model
(5, 29-30). The prevalence-based model quantifies economic costs to
society incurred during a period of time (usually a year) as a result of
the prevalence of disease. The prevalence approach is functional for
measuring the effectiveness of cost control and how well health care
expenditure targets are met. This approach measures the value of
resources lost during a specified period, irrespective of the time of
disease onset. The incidence-based model estimates the lifetime costs of
an illness, based on all cases with onset of disease in a given base
year. The approach adopted depends on the purpose of the analysis (5,
29). Our study estimated the labor productivity loss due to cancer using
an incidence-based approach (the lifetime loss of productivity of those
who died of cancer in 2004) instead of a prevalence-based approach (the
loss of productivity in 2004 of those who died of cancer in 2004 or in
previous years and who otherwise would have been alive in 2004) (22). We
selected this model because the incidence approach is better suited for
decision making about treatment or research strategies as it more
realistically reflects the impact of reduced incidence or improved
outcomes in the context of future costs (5).

We also based our study on the human capital approach, that is
founded on the assertion that social welfare is reduced by disease,
disability, and premature death (4, 6, 31-32). The 'human capital
approach' focuses in measuring and valuating production that is
lost due to morbidity and mortality in a period. This period is equal to
the numbers of years of potential economic contribution of a person to
society (27, 31, 33). A person would have continued to be productive for
a number of years if he or she had not died prematurely from cancer
(13-15). This approach does not measure the value of a life, but
instead, it measures only the value of labor, using earnings or imputed
earnings as a proxy measure (21). Economists at the Centers for Disease
Control and Prevention (CDC) use the human capital approach to value the
morbidity and mortality outcomes in cost-benefits analysis (31, 34).

In various studies, productivity is calculated as the present value
of the sum of earnings and the imputed value of household production
over the lifetime, adjusted for survival, discounting and expected
growth (10, 12-17). In the present study, we estimated the value of lost
earnings that would have been accrued through the labor market and did
not include the non-paid care giving and housekeeping activities like
other studies have done. Without reducing importance of all the above
items, we focused on those components for which we have enough valid
data to report reliable estimates. This will lead us to consider only
productivity in the labor market. Our model also considered the earning
and employment changes over the life cycle, by summing the expected
earnings in each year of forgo ne life over a given life expectancy,
accounting for changes in the probability of employment and earning that
occur from age group to age group, for each sex (21). The component of
earning consisted of money paid directly to individuals in the form of
wage, salary income, and self-employment earnings (34-35).

Following a similar nomenclature of another report (10), we used
the following formula (Formula 1) to estimate the present value of
lifetime earnings (PVLE), that potentially was lost due to premature
mortality from cancer.

[Y.sub.ns] = annual average earnings for all persons of a given sex
with earnings in an age group where the midpoint age is n

[W.sub.ns] = average employment ratio of a given sex in the age
group where the midpoint age is n

[P.sup.n.sub.as] = the approximate probability that an individual
of age a and sex s survives to age n

g = annual rate of growth of labor productivity

i = discount rate

[alpha] = inflation rate

The potential productivity years of life lost (PPYLL) were
estimated according to the total premature cancer deaths and by
cause-specific cancer. The first component of the formula is the sum of
the estimated value of earning for persons in the labor force
([Y.sub.ns] [W.sub.ns] [P.sub.nas]) that takes into account the annual
average earning, labor employment ratio and the probability of survival
for each age group and sex. That estimate was adjusted for changes in
labor productivity (g) and discounted (i) to convert the lifetime
earning into a present value. Changes in labor productivity adjustment
(g) serve to consider the fact that changes in productivity, which is a
function of the availability of capital and technology, lead to real
earnings growth (e.g., through new technological developments). The
discounted rate adjustment is used to express the value of the future
costs in present value. Finally, to express the productivity loss in
constant prices we deflated average earnings using the average of the
last five years of deflator of Gross Product of PR (36). This procedure
is necessary to adjust for the effect of inflation (a). Inflation is an
increase in the general level of prices of goods and services in an
economy over a period usually as measured by the Consumer Price Index
(CPI). Nevertheless, in PR the use and the validity of this indicator as
a measure of inflation has been questioned (37). Therefore, we decided
to use the deflator of the Gross Product of PR. Gross Product deflator
is a measure of the price of all the goods and services included in the
Gross National Product (GNP).

Assumptions

Important assumptions and parameters were used for this model.
First, we assumed that no earnings are earned between the ages of 0 to
15, as the legal age to be hired for employment in PR is 16 years. Also,
the age of legal retirement in PR, 65 years of age, was considered as
the age limit to stay in the labor market. Nevertheless, even though 92%
of people 65 years of age and older opt for retirement, the remaining 8%
represent less than 0.5% of the workforce in the labor market in PR
(38). Additionally, earning capacity included both wage earnings and
employer provided fringe benefits (35). To include total earnings, we
imputed the recommended 22.4% of earning compensation attributed to
fringe benefits (20-21). These benefits include vacation pay, health
insurance, and retirement benefits.

We used the annual rate of productivity growth at 1.8%, as
estimated in PR in a previous study (7). In the basic model, we applied
a discount rate of 3% to employment earning to reflect the present value
of future productivity. This rate is the most commonly used in this type
of study. In fact, CDC currently recommends that a 3% social discount
rate should be used in analyses that require adjusting future costs and
benefits of public health interventions, programs, and policies (31,
39). The discount rate is a financial measure that is used to determine
the present value of future payments. The lower the discount rate, the
higher the present value of future income. A discount rate of 0%
indicates no distinction between present and future costs and benefits.
Sensitivity analysis is recommended anytime there is uncertainty (30,
39). Following previously published studies (10, 14, 21-22, 40), we
compared with the base scenario how the results changed when we applied
different discount rates. In the sensitivity analysis, the discounted
rate varied from 0% to 10%.

Data Sources

Mortality data were obtained for the most recent year of data
publication (2004) provided by the PR Department of Health, through the
Auxiliary Secretariat for Planning and Division Analysis (41). Cancer
deaths were defined as all deaths of persons aged 0-65 years, for which
the primary cause of death was cancer. SEER cause of death recode was
used to classify the cancer deaths by means of the SEER*Stat 6.5.2
software (42). To calculate the life expectancy tables for PR for the
year 2004, we used mortality data from Vital Statistics and population
estimated data from the PR Planning Board. Life expectancy was
calculated by sex; these estimations were calculated with the use of
EpiDat 3.1 software (43). As in other studies, in the absence of
sufficient data for further modeling, persons dying of cancer were
assumed to otherwise have comparable life expectancies of general
population (23, 43). Also, the employment ratio and the average earning
by sex for the year 2005 were estimated using the Public Use Microdata
Sample (PUMS) of Census Bureau's PR Community Survey (PRCS) (35).
This survey collects information about population and housing
characteristics for the nation, states, cities, counties, metropolitan
areas, and communities on a continuous basis. The collection for the
PRCS began in January 2005, with an annual sample size of approximately
36,000 addresses. For that reason we decided to use the 2005 file,
instead of that for 2004.

Results

Employment and earnings estimated, by sex and age groups, for the
population of PR are presented in Table 1. In all age groups, earnings
and employment ratios were higher for males than for females. For both
sexes, employment ratios and earnings were smallest in the youngest age
groups. These earnings and employment ratios increased substantially in
later ages and dropped again before the usual age of retirement at 65
years of age.

The number of pre-retirement deaths from all causes of death and
attributed to cancer, the PPYLL and the estimates of the PVLE for the
year 2004 are shown in Table 2. In total, 8,953 persons died before the
age of 65 in PR in 2004, of which 1,515 persons died due to cancer.
Premature cancer deaths represent nearly 31% of the total cancer deaths.
These cancer deaths accounted for loss of 17,475 PPYLL due to premature
cancer mortality. Breast cancer had the largest relative contribution in
terms of premature death and PPYLL, followed by colorectal cancer and
lung and bronchus. The estimated PVLE from all malignant cancer in 2004
was approximately $64.2 million (in constant value), assuming a discount
rate of 3%. This corresponds to 13.8% of total productivity cost in the
labor market ($464 million) in PR (Table 2). Lung cancer premature
deaths accounted for 11.8% ($7.6 million) of the total PVLE. The other
most costly cancers were colorectal cancer ($7.5 million) and breast
cancer ($6.6 million), which accounted for 11.7% and 10.3%,
respectively, of the total PVLE loss. These three types of cancer
represented more than a third (33.6%) of the total PVLE costs. By
contrast, prostate cancer (the type of cancer that causes more deaths in
males) accounted for only 2.6% of the total cost. When we analyzed the
losses related to hematopoietic cancers and myeloma, and consider them
as a total, these losses nearly reached the total costs of breast
cancer.

More than 30% of the labor productivity loss was caused by the
types of cancer directly related to tobacco use (lung and bronchus, oral
cavity and pharynx, esophagus, pancreas, stomach and larynx). As well,
the most costly cancers per death were testis cancer ($71,347.93),
followed by kidney and renal pelvis cancer ($69,110.16), mesothelioma
($67,438.08), myeloma ($50,929.26) and oral cavity and pharynx
($59,194.52). Although there were few cancer deaths from these types of
cancer, as compared to other cancer types, the largest proportion of
deaths occurred in younger age groups.

Figure 1 shows the PVLE, by sex, for the major cancer types. The
productivity loss due to all types of cancer combined was two times
higher for men than for women ($21.6 vs. 42.7 million). Moreover,
colorectal cancer, the second type of cancer that causes more PVLE for
both men and women, in fact produces more than twice the PVLE in men as
compared to women. We also found that the types of cancer that cause
more PVLE differ by sex (Figure 1). For males, the most expensive
cancers in terms of lost productivity are lung and bronchus ($6.2
million), colorectal ($5.3 million), liver and intrahepatic bile duct
($4.7 million) and oral cavity and pharynx ($3.4 million). For females,
breast cancer is the most costly cancer ($6.4 million); almost three
times more expensive than the second one (colorectal cancer, $2.2
million). The next most costly cancers for women were lung and bronchus
($1.4 million), followed by ovarian ($1.2 million) and non-Hodgkin
lymphoma ($1.0 million).

Given that the estimated PVLE is sensitive to the discount rate
chosen, we conducted a sensitivity analysis (using discount rates
varying from 0% to 10%), in order to provide a range of possible
lifetime productivity losses. Figure 2 illustrates the results of this
analysis that produced productivity losses for premature mortality
ranging from $28.9 million (using a discount rate of 10%) to $101.9
million (using a discount rate of 0%).

Discussion

This study describes, for the first time, the economic impact of
cancer in PR. Specifically, it describes the extent of the potential
losses due to premature cancer death for the Island's economy. The
total productivity losses in the labor market due to cancer in PR in
2004 were approximately $64 million (at a 3% discount rate and in
constant value). These estimates represent nearly 14% of the total
productivity loss in the labor market ($464 million) for 2004 in PR.
Therefore, although cancer is a disease that usually occurs late in the
life cycle, the losses of productivity caused by premature cancer death
are a great burden in PR. This could be explained, in part, by a change
in the cancer incidence pattern among persons aged <65 years. For the
period 1987-2004, cancer incidence trends showed a significant increase
(APC= 2.7%, p<0.05) in people <65 years of age, while, trends in
people aged 65 years of age and older remained stable (APC = -0.1%,
p>0.05) (44). Although overall cancer mortality trends have decreased
in average 1.0% annually from 1987-2004 (similar in persons aged <65
and >=65 years), cancer remains the leading cause of premature death
in PR, representing nearly 17% of total deaths in 2004 (45).

Although it is important to notice that cost studies generated with
different methods are not directly comparable, we can recognize that the
cancer sites that generate most productivity loss in PR (lung and
bronchus, colorectal, and breast cancer) also represent the greater
productivity cost in the US, representing 27.4%, 9.0% and 7.6%,
respectively (21). These types of cancer are either highly preventable
or can be diagnosed early (46-47). Furthermore, it is evident that a
large proportion of the productivity loss causing cancers are those
related to tobacco use. This risk factor is associated with increased
risk for at least 15 cancer types including lung and bronchus, oral
cavity and pharynx, and esophagus (46-47). In PR, it has been estimated
that the attributable risk of oral cavity and pharynx due to alcohol and
tobacco use is around 76% (95% CI: 65-87%) for men and 52% (95%
CI:28-75%) for women (48). Also, the prevalence of cigarette use among
adults in 2004 was 12.6%, although it showed a decrease over the last
decade from 14.5% in 1996 to 11.7% in 2008 (49). Thus, even though the
prevalence of current cigarette smoking is not as high as in the US
(20.9%) (50), we should continue to promote public policies focused on
reducing the use of tobacco in PR, if we expect to decrease the
productivity loss in a significant way.

Significant costs differences were also observed by sex. The types
of cancer linked to tobacco consumption had a higher cost for men as
compared to women. These findings are consistent with the differences in
the prevalence of tobacco use in men and women in PR. In 2004, the
prevalence of current smoking in males was 17.4%, compared with 8.4% in
females (49). In addition, PVLE for liver and intrahepatic bile duct
cancer was higher in males compared with females. These results may be
associated with a higher prevalence of alcohol consumption, hepatitis B
(HBV), hepatitis C (HCV), all of them risk factors for hepatic
cirrhosis, a well-known pre-malignant condition for developing liver
cancer, and more common among males. In 2004, the prevalence of men
having more than two drinks per day was 4.6% compared with 2.0% in
females (49). Also, the prevalence for HCV in men was 4-fold as compared
to women (4.0% vs. 1.0%) among the PR population (51). Moreover, the
prevalence of HBV was twice as frequent in males, (4.3%) as compared to
females (2.5%) (51).

We also observed that oral cavity and pharynx cancer had a very
high cost per death, although this is not a typical cancer among persons
aged <65 years. The median age at diagnosis is 64 years and the
median age for death is 68 years (52), this type of cancer also affects
adversely more males in the working age. This is of particular relevance
as oral cancer is still among the top leading cancer types in men in PR
(52). It is important to note that the median age of death from oral
cavity and pharynx cancer is less than the median age at diagnosis for
lung and bronchus cancer (70 years) (53). Given that oral cavity and
pharynx cancer share an important risk factor with lung cancer, tobacco
use, we can hypothesize that deaths due to the former in some way
deplete the pool of people susceptible to developing and dying from lung
cancer (tobacco users) years later. If we could control for oral and
pharynx cancer death, smokers would still be at risk of developing and
dying from lung cancer.

Another important finding from our study is that although mortality
from stomach and from esophagus cancers have decreased since the
1950's in PR (54-55), both remain highly costly diseases, partly
because of the poor survival typical of these types of cancer.
Meanwhile, leukemia, myeloma, non-Hodgkin lymphoma, and brain and
central nervous system tumors have a substantial burden in both sexes.
This impact could be attributed to the greater mortality of many of
these types of cancer in children, producing a higher PVLE. Although
childhood cancer accounts for about 1% of all cancers in PR, leukemia,
brain tumors and lymphoma account for the vast majority of childhood
cancer related deaths.

It is important to note that breast cancer, the most common cancer
among females in PR, is more costly than prostate cancer, the most
common cancer among men. This study demonstrated that although men have
higher wages, employment, and mortality from cancer than women, breast
cancer ranks as the third type of cancer causing more loss of
productivity in PR. These results are due, in part, to the higher
proportion of younger females dying of breast cancer, while prostate
cancer affects primarily older men. While the median age at diagnosis
for breast cancer is 59 years, and the median age at death is 63 years,
for prostate cancer the median age at diagnosis is 10 years later (69
years at diagnosis) and the median age at death is 82, well beyond
retirement age (56-57). Although we observed that Puerto Rican females
younger than 65 years of age showed a significant reduction in breast
cancer mortality rates (58), potentially due to the progress made in
reducing breast cancer mortality, it remains a deadly disease among
working age females and a costly one for the Puerto Rican society.

Implications for health policy

In economic terms, cancer affects the most important productive
resource, the human capital. While the productivity loss due to cancer
death represents a very high cost for society, someone may be tempted to
consider as a benefit the payment of pensions that will never be paid
due to premature deaths. This notion, however, does not consider that
public health interventions do not have as final objective the saving of
monetary expenses or the budgetary control (25). The primary target of
any intervention in public health must be the prolongation of survival
and improvement of the quality of life of cancer survivors. The
considerations in which premature mortality have a saving component
could jeopardize the achievement of this objective (25).

Interventions in cancer must be implemented through a comprehensive
public policy that includes attention, not only to the medical aspect,
but also to social and economic issues, including scientific research
and development. According to the PR Comprehensive Cancer Control Plan
2008-2012 (59) it is necessary to have a comprehensive approach to reach
the goal of cancer control and prevention in PR. In order to achieve
these objectives, it is necessary to create accurate and reliable
estimates of cancer-related cost and others empirical studies to improve
how to allocate limited economic resources for cancer control. These
types of studies represent an important analytic tool for the design and
implementation of public health policy.

Investments in programs that decrease lung, colorectal, breast, and
liver cancer mortality are likely to generate the major decline in
productivity loss in PR. As a fundamental part to maximize the social
well-being, it is necessary to place emphasis in cancer prevention. The
leading cancer sites that generate most productivity losses are highly
preventable or can be diagnosed early. One of the most important
objectives for cancer control programs, from an economic perspective of
cost in terms of labor productivity, is the investment in programs that
reduce the types of cancer directly related to the use of tobacco in our
society.

Limitations and Recommendations

Various limitations of this study should be acknowledged. This kind
of study can demonstrate which type of cancer may require increased
allocation of prevention or treatment resources, but is limited in
determining how resources are to be allocated, as it does not measure
benefits. In addition, studies can vary by perspective, sources of data,
inclusion of indirect costs, and the period of costs, which can limit
the comparability of findings with the present study (19). In addition,
the estimates do not include the value of care giving, household work,
and earning from informal economy, contributions that could be more
important for females given their traditional roles in our society.
Also, it is important to point out that productivity loss due to
premature mortality is only one component of a framework for estimating
the economic cost of cancer in PR. The estimations presented in this
study do not represent the total of productivity loss in PR's
labor-market due to cancer. In addition, an important aspect that was
not considered in this study was the labor productivity loss associated
to disability. Although this study focused in mortality, disability
represents a significant problem that has great impact in the labor
market. The improvements in early detection and advances in treatment of
cancer have increased the survival rate for all cancers in general,
raising the prevalence of people diagnosed with cancer (60). People
diagnosed with cancer have a high probability of suffering a loss of
productive capacity, consequently, affecting the productivity in the
labor market. One in six cancer survivor workers in the US report they
were unable to work and an additional 7% indicated that they were
limited in the amount and type of work they could perform (61-62).
Therefore, future studies in PR should focus on obtaining reliable data
to estimate the total productivity cost, including costs caused by
disability, as the exclusion of disability from these estimates can
result in an underestimation of the total productivity loss due to
cancer.

Furthermore, if direct costs (medical expenses resulting from
cancer) were added to the COI estimates, the economic impact of cancer
will be substantially higher. According to a study performed in PR,
20.4% of the Gross National Product (GNP) in PR corresponds to health
expenditures (63). This is twice as much as in Europe and 25% more than
in the US. Therefore, the direct cost of cancer can be extremely costly
and represents a great burden for PR (59, 63). These limitations suggest
that the estimates of productive cost of cancer in PR could be even
greater than those estimated in the current analysis. But, as mentioned
earlier, we considered only productivity loss in the labor market
because we focused our analysis on those components for which we had
valid data to report reliable estimates. The impact of premature
mortality due to cancer in the economy of PR evidenced in this study
confirms the need for funding to increase research capacity in this
area. It is essential to estimate the other components of COI in order
to provide more accurate information of the burden of cancer.
Consequently, informed decisions can be taken to allocate resources more
efficiently for cancer control.

Conclusion

Our study shows a broader picture that includes the economic
dimension of cancer as a health problem in our society. The leading
cancer sites that generate most productivity losses are highly
preventable or can be diagnosed early. We have identified that the mayor
labor productivity loss was caused by the types of cancer directly
related to tobacco use. Our results also show that despite the
widespread availability of breast and colorectal cancer screening and
the efforts to reduce the use of tobacco and other risk factors for
developing cancer, it is evident that a substantial health and economic
impact associated with these types of cancer remains. Future research
including those that consider the other components of COI should be
developed and considered within the framework for health and cancer
control policies.

Acknowledgements

This work was supported, in part, by the National Program of Cancer
Registries (NPCR) of the CDC, Grant #1U58DP000782-03 and NCI Grant
#U54CA96297.

(22.) Ekwueme DU, Chesson HW, Zhang KB, Balamurugan A. Years of
potential life lost and productivity costs because of cancer mortality
and for specific cancer sites where human papillomavirus may be a risk
factor for carcinogenesis-United States, 2003. Cancer
2008;113:2936-2945.

(49.) Centers for Disease Control and Prevention (CDC). Behavioral
Risk Factor Surveillance System Survey Data. Atlanta, Georgia: U.S.
Department of Health and Human Services, Centers for Disease Control and
Prevention; 2008.

(50.) Centers for Disease Control and Prevention. Behavioral Risk
Factor Surveillance System Survey Data. Atlanta, Georgia: U.S.:
Department of Health and Human Services, Centers for Disease Control and
Prevention, 2004.

(61.) Feuerstein M, Harrington CB. Recommendations for the U.S.
National Occupational Research Agenda: Research on cancer survivorship
and musculoskeletal disorders and work disability. J Occup Rehabil
2006;16:1-5.

* Puerto Rico Central Cancer Registry, Cancer Control and
Population Sciences Program, University of Puerto Rico Comprehensive
Cancer Center, San Juan, PR; ([dagger]) Department of Health Services
Administration, Graduate School of Public Health, Medical Sciences
Campus, University of Puerto Rico, San Juan, PR; ([section]) Department
of Economics, School of Social Sciences, Rio Piedras Campus, University
of Puerto Rico, San Juan, PR; ([double dagger]) Department of
Biostatistics and Epidemiology, Graduate School of Public Health,
Medical Sciences Campus, University of Puerto Rico, San Juan, PR;
([dagger]) ([dagger]) Cancer Control and Population Sciences Program,
University of Puerto Rico Comprehensive Cancer Center, San Juan, PR;
([paragraph]) UPR-MDACC Partnership for Excellence in Cancer Research
Program, Medical Sciences Campus, University of Puerto Rico, San Juan,
PR